{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Riskfolio-Lib Tutorial: \n",
    "<br>__[Financionerioncios](https://financioneroncios.wordpress.com)__\n",
    "<br>__[Orenji](https://www.orenj-i.net)__\n",
    "<br>__[Riskfolio-Lib](https://riskfolio-lib.readthedocs.io/en/latest/)__\n",
    "<br>__[Dany Cajas](https://www.linkedin.com/in/dany-cajas/)__\n",
    "<a href='https://ko-fi.com/B0B833SXD' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://cdn.ko-fi.com/cdn/kofi1.png?v=2' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a> \n",
    "\n",
    "## Tutorial 13: Riskfolio-Lib and Xlwings\n",
    "\n",
    "## 1. Downloading the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  25 of 25 completed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "yf.pdr_override()\n",
    "pd.options.display.float_format = '{:.4%}'.format\n",
    "\n",
    "# Date range\n",
    "start = '2016-01-01'\n",
    "end = '2019-12-30'\n",
    "\n",
    "# Tickers of assets\n",
    "assets = ['JCI', 'TGT', 'CMCSA', 'CPB', 'MO', 'APA', 'MMC', 'JPM',\n",
    "          'ZION', 'PSA', 'BAX', 'BMY', 'LUV', 'PCAR', 'TXT', 'TMO',\n",
    "          'DE', 'MSFT', 'HPQ', 'SEE', 'VZ', 'CNP', 'NI', 'T', 'BA']\n",
    "assets.sort()\n",
    "\n",
    "# Downloading data\n",
    "data = yf.download(assets, start = start, end = end)\n",
    "data = data.loc[:,('Adj Close', slice(None))]\n",
    "data.columns = assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>-2.0257%</td>\n",
       "      <td>0.4057%</td>\n",
       "      <td>0.4035%</td>\n",
       "      <td>1.9693%</td>\n",
       "      <td>0.0180%</td>\n",
       "      <td>0.9305%</td>\n",
       "      <td>0.3678%</td>\n",
       "      <td>0.5783%</td>\n",
       "      <td>0.9483%</td>\n",
       "      <td>-1.1954%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.5881%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>2.8236%</td>\n",
       "      <td>0.9758%</td>\n",
       "      <td>0.6987%</td>\n",
       "      <td>1.7539%</td>\n",
       "      <td>-0.1730%</td>\n",
       "      <td>0.2410%</td>\n",
       "      <td>1.3734%</td>\n",
       "      <td>-1.0857%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-06</th>\n",
       "      <td>-11.4863%</td>\n",
       "      <td>-1.5879%</td>\n",
       "      <td>0.2412%</td>\n",
       "      <td>-1.7557%</td>\n",
       "      <td>-0.7727%</td>\n",
       "      <td>-1.2473%</td>\n",
       "      <td>-0.1736%</td>\n",
       "      <td>-1.1239%</td>\n",
       "      <td>-3.5867%</td>\n",
       "      <td>-0.9551%</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5547%</td>\n",
       "      <td>0.0212%</td>\n",
       "      <td>0.1592%</td>\n",
       "      <td>-1.5646%</td>\n",
       "      <td>-0.1466%</td>\n",
       "      <td>-1.0155%</td>\n",
       "      <td>-0.7653%</td>\n",
       "      <td>-3.0048%</td>\n",
       "      <td>-0.9034%</td>\n",
       "      <td>-2.9145%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-07</th>\n",
       "      <td>-5.1389%</td>\n",
       "      <td>-4.1922%</td>\n",
       "      <td>-1.6573%</td>\n",
       "      <td>-2.7699%</td>\n",
       "      <td>-1.1047%</td>\n",
       "      <td>-1.9769%</td>\n",
       "      <td>-1.2207%</td>\n",
       "      <td>-0.8855%</td>\n",
       "      <td>-4.6059%</td>\n",
       "      <td>-2.5394%</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.2066%</td>\n",
       "      <td>-3.0309%</td>\n",
       "      <td>-1.0410%</td>\n",
       "      <td>-3.1557%</td>\n",
       "      <td>-1.6148%</td>\n",
       "      <td>-0.2700%</td>\n",
       "      <td>-2.2845%</td>\n",
       "      <td>-2.0570%</td>\n",
       "      <td>-0.5492%</td>\n",
       "      <td>-3.0019%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-08</th>\n",
       "      <td>0.2737%</td>\n",
       "      <td>-2.2705%</td>\n",
       "      <td>-1.6037%</td>\n",
       "      <td>-2.5425%</td>\n",
       "      <td>0.1099%</td>\n",
       "      <td>-0.2241%</td>\n",
       "      <td>0.5707%</td>\n",
       "      <td>-1.6402%</td>\n",
       "      <td>-1.7641%</td>\n",
       "      <td>-0.1649%</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.1538%</td>\n",
       "      <td>-1.1366%</td>\n",
       "      <td>-0.7308%</td>\n",
       "      <td>-0.1448%</td>\n",
       "      <td>0.0895%</td>\n",
       "      <td>-3.3839%</td>\n",
       "      <td>-0.1117%</td>\n",
       "      <td>-1.1386%</td>\n",
       "      <td>-0.9719%</td>\n",
       "      <td>-1.1254%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>-4.3384%</td>\n",
       "      <td>0.1693%</td>\n",
       "      <td>-1.6851%</td>\n",
       "      <td>-1.0215%</td>\n",
       "      <td>0.0915%</td>\n",
       "      <td>-1.1791%</td>\n",
       "      <td>0.5674%</td>\n",
       "      <td>0.5287%</td>\n",
       "      <td>0.6616%</td>\n",
       "      <td>0.0330%</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6435%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.9869%</td>\n",
       "      <td>-0.1450%</td>\n",
       "      <td>1.2224%</td>\n",
       "      <td>1.4570%</td>\n",
       "      <td>0.5367%</td>\n",
       "      <td>-0.4607%</td>\n",
       "      <td>0.5800%</td>\n",
       "      <td>-1.9918%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 APA       BA      BAX      BMY    CMCSA      CNP      CPB  \\\n",
       "Date                                                                         \n",
       "2016-01-05  -2.0257%  0.4057%  0.4035%  1.9693%  0.0180%  0.9305%  0.3678%   \n",
       "2016-01-06 -11.4863% -1.5879%  0.2412% -1.7557% -0.7727% -1.2473% -0.1736%   \n",
       "2016-01-07  -5.1389% -4.1922% -1.6573% -2.7699% -1.1047% -1.9769% -1.2207%   \n",
       "2016-01-08   0.2737% -2.2705% -1.6037% -2.5425%  0.1099% -0.2241%  0.5707%   \n",
       "2016-01-11  -4.3384%  0.1693% -1.6851% -1.0215%  0.0915% -1.1791%  0.5674%   \n",
       "\n",
       "                 DE      HPQ      JCI  ...       NI     PCAR      PSA  \\\n",
       "Date                                   ...                              \n",
       "2016-01-05  0.5783%  0.9483% -1.1954%  ...  1.5881%  0.0212%  2.8236%   \n",
       "2016-01-06 -1.1239% -3.5867% -0.9551%  ...  0.5547%  0.0212%  0.1592%   \n",
       "2016-01-07 -0.8855% -4.6059% -2.5394%  ... -2.2066% -3.0309% -1.0410%   \n",
       "2016-01-08 -1.6402% -1.7641% -0.1649%  ... -0.1538% -1.1366% -0.7308%   \n",
       "2016-01-11  0.5287%  0.6616%  0.0330%  ...  1.6435%  0.0000%  0.9869%   \n",
       "\n",
       "                SEE        T      TGT      TMO      TXT       VZ     ZION  \n",
       "Date                                                                       \n",
       "2016-01-05  0.9758%  0.6987%  1.7539% -0.1730%  0.2410%  1.3734% -1.0857%  \n",
       "2016-01-06 -1.5646% -0.1466% -1.0155% -0.7653% -3.0048% -0.9034% -2.9145%  \n",
       "2016-01-07 -3.1557% -1.6148% -0.2700% -2.2845% -2.0570% -0.5492% -3.0019%  \n",
       "2016-01-08 -0.1448%  0.0895% -3.3839% -0.1117% -1.1386% -0.9719% -1.1254%  \n",
       "2016-01-11 -0.1450%  1.2224%  1.4570%  0.5367% -0.4607%  0.5800% -1.9918%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating returns\n",
    "\n",
    "Y = data[assets].pct_change().dropna()\n",
    "\n",
    "display(Y.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Estimating Mean Variance Portfolios\n",
    "\n",
    "### 2.1 Calculating the portfolio that maximizes Sharpe ratio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>weights</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.1590%</td>\n",
       "      <td>11.5019%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.4807%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.8193%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>10.8262%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>7.1805%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.2738%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE  \\\n",
       "weights 0.0000% 6.1590% 11.5019% 0.0000% 0.0000% 8.4807% 0.0000% 3.8193%   \n",
       "\n",
       "            HPQ     JCI  ...       NI    PCAR     PSA     SEE       T     TGT  \\\n",
       "weights 0.0000% 0.0000%  ... 10.8262% 0.0000% 0.0000% 0.0000% 0.0000% 7.1805%   \n",
       "\n",
       "            TMO     TXT      VZ    ZION  \n",
       "weights 0.0000% 0.0000% 4.2738% 0.0000%  \n",
       "\n",
       "[1 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import riskfolio.Portfolio as pf\n",
    "\n",
    "# Building the portfolio object\n",
    "port = pf.Portfolio(returns=Y)\n",
    "# Calculating optimum portfolio\n",
    "\n",
    "# Select method and estimate input parameters:\n",
    "\n",
    "method_mu='hist' # Method to estimate expected returns based on historical data.\n",
    "method_cov='hist' # Method to estimate covariance matrix based on historical data.\n",
    "\n",
    "port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)\n",
    "\n",
    "# Estimate optimal portfolio:\n",
    "\n",
    "model='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)\n",
    "rm = 'MV' # Risk measure used, this time will be variance\n",
    "obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe\n",
    "hist = True # Use historical scenarios for risk measures that depend on scenarios\n",
    "rf = 0 # Risk free rate\n",
    "l = 0 # Risk aversion factor, only useful when obj is 'Utility'\n",
    "\n",
    "w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)\n",
    "\n",
    "display(w.T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Plotting portfolio composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import riskfolio.PlotFunctions as plf\n",
    "\n",
    "# Plotting the composition of the portfolio\n",
    "\n",
    "fig_1, ax_1 = plt.subplots(figsize=(10,6))\n",
    "\n",
    "ax_1 = plf.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = \"tab20\",\n",
    "                    height=6, width=10, ax=ax_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Calculate efficient frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>APA</th>\n",
       "      <th>BA</th>\n",
       "      <th>BAX</th>\n",
       "      <th>BMY</th>\n",
       "      <th>CMCSA</th>\n",
       "      <th>CNP</th>\n",
       "      <th>CPB</th>\n",
       "      <th>DE</th>\n",
       "      <th>HPQ</th>\n",
       "      <th>JCI</th>\n",
       "      <th>...</th>\n",
       "      <th>NI</th>\n",
       "      <th>PCAR</th>\n",
       "      <th>PSA</th>\n",
       "      <th>SEE</th>\n",
       "      <th>T</th>\n",
       "      <th>TGT</th>\n",
       "      <th>TMO</th>\n",
       "      <th>TXT</th>\n",
       "      <th>VZ</th>\n",
       "      <th>ZION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>5.2634%</td>\n",
       "      <td>4.3887%</td>\n",
       "      <td>2.1705%</td>\n",
       "      <td>6.9871%</td>\n",
       "      <td>3.2390%</td>\n",
       "      <td>0.0790%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8377%</td>\n",
       "      <td>...</td>\n",
       "      <td>11.4508%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>14.9184%</td>\n",
       "      <td>0.1628%</td>\n",
       "      <td>6.4196%</td>\n",
       "      <td>4.0904%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>8.3446%</td>\n",
       "      <td>0.0001%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.0325%</td>\n",
       "      <td>8.4718%</td>\n",
       "      <td>0.8579%</td>\n",
       "      <td>1.9327%</td>\n",
       "      <td>8.5940%</td>\n",
       "      <td>2.1945%</td>\n",
       "      <td>1.4376%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.1060%</td>\n",
       "      <td>...</td>\n",
       "      <td>13.4410%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.2132%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>4.1682%</td>\n",
       "      <td>5.5285%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.4731%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>2.8407%</td>\n",
       "      <td>9.3407%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.5588%</td>\n",
       "      <td>9.1990%</td>\n",
       "      <td>1.7699%</td>\n",
       "      <td>1.8516%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.2108%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.2140%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>6.5518%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.1594%</td>\n",
       "      <td>6.0608%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>9.9971%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.4597%</td>\n",
       "      <td>9.8935%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.0711%</td>\n",
       "      <td>9.6311%</td>\n",
       "      <td>1.2504%</td>\n",
       "      <td>2.0914%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>14.7829%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.9064%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.9201%</td>\n",
       "      <td>6.4433%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.5067%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0000%</td>\n",
       "      <td>3.9674%</td>\n",
       "      <td>10.3314%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5839%</td>\n",
       "      <td>9.9784%</td>\n",
       "      <td>0.6012%</td>\n",
       "      <td>2.2744%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>...</td>\n",
       "      <td>15.1468%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>1.3826%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.5558%</td>\n",
       "      <td>6.7335%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>0.0000%</td>\n",
       "      <td>10.8300%</td>\n",
       "      <td>0.0000%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      APA      BA      BAX     BMY   CMCSA     CNP     CPB      DE     HPQ  \\\n",
       "0 0.0000% 0.0000%  5.2634% 4.3887% 2.1705% 6.9871% 3.2390% 0.0790% 0.0000%   \n",
       "1 0.0000% 2.0325%  8.4718% 0.8579% 1.9327% 8.5940% 2.1945% 1.4376% 0.0000%   \n",
       "2 0.0000% 2.8407%  9.3407% 0.0000% 1.5588% 9.1990% 1.7699% 1.8516% 0.0000%   \n",
       "3 0.0000% 3.4597%  9.8935% 0.0000% 1.0711% 9.6311% 1.2504% 2.0914% 0.0000%   \n",
       "4 0.0000% 3.9674% 10.3314% 0.0000% 0.5839% 9.9784% 0.6012% 2.2744% 0.0000%   \n",
       "\n",
       "      JCI  ...       NI    PCAR      PSA     SEE       T     TGT     TMO  \\\n",
       "0 2.8377%  ... 11.4508% 0.0000% 14.9184% 0.1628% 6.4196% 4.0904% 0.0000%   \n",
       "1 1.1060%  ... 13.4410% 0.0000%  9.2132% 0.0000% 4.1682% 5.5285% 0.0000%   \n",
       "2 0.2108%  ... 14.2140% 0.0000%  6.5518% 0.0000% 3.1594% 6.0608% 0.0000%   \n",
       "3 0.0000%  ... 14.7829% 0.0000%  3.9064% 0.0000% 1.9201% 6.4433% 0.0000%   \n",
       "4 0.0000%  ... 15.1468% 0.0000%  1.3826% 0.0000% 0.5558% 6.7335% 0.0000%   \n",
       "\n",
       "      TXT       VZ    ZION  \n",
       "0 0.0000%  8.3446% 0.0001%  \n",
       "1 0.0000%  9.4731% 0.0000%  \n",
       "2 0.0000%  9.9971% 0.0000%  \n",
       "3 0.0000% 10.5067% 0.0000%  \n",
       "4 0.0000% 10.8300% 0.0000%  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "points = 50 # Number of points of the frontier\n",
    "\n",
    "frontier = port.efficient_frontier(model=model, rm=rm, points=points, rf=rf, hist=hist)\n",
    "\n",
    "display(frontier.T.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Efficient Frontier Mean - Standard Deviation (MV)'}, xlabel='Expected Risk - Standard Deviation (MV)', ylabel='Expected Return'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the efficient frontier\n",
    "\n",
    "label = 'Max Risk Adjusted Return Portfolio' # Title of point\n",
    "mu = port.mu # Expected returns\n",
    "cov = port.cov # Covariance matrix\n",
    "returns = port.returns # Returns of the assets\n",
    "\n",
    "fig_2, ax_2 = plt.subplots(figsize=(10,6))\n",
    "\n",
    "plf.plot_frontier(w_frontier=frontier, mu=mu, cov=cov, returns=returns, rm=rm,\n",
    "                  rf=rf, alpha=0.01, cmap='viridis', w=w, label=label,\n",
    "                  marker='*', s=16, c='r', height=6, width=10, ax=ax_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':\"Efficient Frontier's Assets Structure\"}>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting efficient frontier composition\n",
    "\n",
    "fig_3, ax_3 = plt.subplots(figsize=(10,6))\n",
    "\n",
    "plf.plot_frontier_area(w_frontier=frontier, cmap=\"tab20\", height=6, width=10, ax=ax_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Combining Riskfolio-Lib and Xlwings\n",
    "\n",
    "### 3.1 Creating an Empty Excel Workbook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xlwings as xw\n",
    "\n",
    "# Creating an empty Excel Workbook\n",
    "\n",
    "wb = xw.Book()  \n",
    "sheet1 = wb.sheets[0]\n",
    "sheet1.name = 'Charts'\n",
    "sheet2 = wb.sheets.add('Frontier')\n",
    "sheet3 = wb.sheets.add('Optimal Weights')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Adding Pictures to Sheet 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Picture 'Composition' in <Sheet [Libro2]Charts>>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sheet1.pictures.add(fig_1, name = \"Weights\",\n",
    "                    update = True, \n",
    "                    top = sheet1.range(\"A1\").top,\n",
    "                    left = sheet1.range(\"A1\").left)\n",
    "\n",
    "sheet1.pictures.add(fig_2, name = \"Frontier\",\n",
    "                    update = True, \n",
    "                    top = sheet1.range(\"M1\").top,\n",
    "                    left = sheet1.range(\"M1\").left)\n",
    "\n",
    "sheet1.pictures.add(fig_3, name = \"Composition\",\n",
    "                    update = True, \n",
    "                    top = sheet1.range(\"A30\").top,\n",
    "                    left = sheet1.range(\"A30\").left)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://raw.githubusercontent.com/dcajasn/Riskfolio-Lib/master/examples/Fig1.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Adding Data to Sheet 2 and Sheet 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Writing the weights of the frontier in the Excel Workbook\n",
    "\n",
    "sheet2.range('A1').value = frontier.applymap('{:.6%}'.format)\n",
    "\n",
    "# Writing the optimal weights in the Excel Workbook\n",
    "\n",
    "sheet3.range('A1').value = w.applymap('{:.6%}'.format)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://raw.githubusercontent.com/dcajasn/Riskfolio-Lib/master/examples/Fig2.png\">\n",
    "<img src=\"https://raw.githubusercontent.com/dcajasn/Riskfolio-Lib/master/examples/Fig3.png\">"
   ]
  }
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